code: def vonmises(
      random_state,
      mu,
      kappa,
      size=None,
      chunk_size=None,
      gpu=None,
      dtype=None,
  ):
      r"""
      Draw samples from a von Mises distribution.
  
      Samples are drawn from a von Mises distribution with specified mode
      (mu) and dispersion (kappa), on the interval [-pi, pi].
  
      The von Mises distribution (also known as the circular normal
      distribution) is a continuous probability distribution on the unit
      circle.  It may be thought of as the circular analogue of the normal
      distribution.
  
      Parameters
      ----------
      mu : float or array_like of floats
          Mode ("center") of the distribution.
      kappa : float or array_like of floats
          Dispersion of the distribution, has to be >=0.
      size : int or tuple of ints, optional
          Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
          ``m * n * k`` samples are drawn.  If size is ``None`` (default),
          a single value is returned if ``mu`` and ``kappa`` are both scalars.
          Otherwise, ``np.broadcast(mu, kappa).size`` samples are drawn.
      chunk_size : int or tuple of int or tuple of ints, optional
          Desired chunk size on each dimension
      gpu : bool, optional
          Allocate the tensor on GPU if True, False as default
      dtype : data-type, optional
        Data-type of the returned tensor.
  
      Returns
      -------
      out : Tensor or scalar
          Drawn samples from the parameterized von Mises distribution.
  
      See Also
      --------
      scipy.stats.vonmises : probability density function, distribution, or
          cumulative density function, etc.
  
      Notes
      -----
      The probability density for the von Mises distribution is
  
      .. math:: p(x) = \frac{e^{\kappa cos(x-\mu)}}{2\pi I_0(\kappa)},
  
      where :math:`\mu` is the mode and :math:`\kappa` the dispersion,
      and :math:`I_0(\kappa)` is the modified Bessel function of order 0.
  
      The von Mises is named for Richard Edler von Mises, who was born in
      Austria-Hungary, in what is now the Ukraine.  He fled to the United
      States in 1939 and became a professor at Harvard.  He worked in
      probability theory, aerodynamics, fluid mechanics, and philosophy of
      science.
  
      References
      ----------
      .. [1] Abramowitz, M. and Stegun, I. A. (Eds.). "Handbook of
             Mathematical Functions with Formulas, Graphs, and Mathematical
             Tables, 9th printing," New York: Dover, 1972.
      .. [2] von Mises, R., "Mathematical Theory of Probability
             and Statistics", New York: Academic Press, 1964.
  
      Examples
      --------
      Draw samples from the distribution:
  
      >>> import mars.tensor as mt
  
      >>> mu, kappa = 0.0, 4.0 # mean and dispersion
      >>> s = mt.random.vonmises(mu, kappa, 1000)
  
      Display the histogram of the samples, along with
      the probability density function:
  
      >>> import matplotlib.pyplot as plt
      >>> from scipy.special import i0
      >>> plt.hist(s.execute(), 50, normed=True)
      >>> x = mt.linspace(-mt.pi, mt.pi, num=51)
      >>> y = mt.exp(kappa*mt.cos(x-mu))/(2*mt.pi*i0(kappa))
      >>> plt.plot(x.execute(), y.execute(), linewidth=2, color='r')
      >>> plt.show()
      """
      if dtype is None:
          dtype = (
              np.random.RandomState()
              .vonmises(
                  handle_array(mu), handle_array(kappa), size=(0,)
              )
              .dtype
          )
  
      size = random_state._handle_size(size)
      seed = gen_random_seeds(1, random_state.to_numpy())[0]
      op = TensorVonmises(size=size, seed=seed, gpu=gpu, dtype=dtype)
      return op(mu, kappa, chunk_size=chunk_size)
  
file_path: mars/mars/tensor/random/vonmises.py
imports: import numpy
  from ...None import opcodes
  from ...serialization.serializables import AnyField
  from ..utils import gen_random_seeds
  from .core import TensorRandomOperandMixin, handle_array, TensorDistribution
label_desc: Use image node_id 1 for calling a global function with example usage: vonmises(random_state, mu, kappa, size, chunk_size, gpu, dtype) and returns: op